Visual Dialog

Deep Residual Learning for Image Recognition

He, K., Zhang, X., Ren, S., & Sun, J. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.90 · Cited by 235,474 · see citing works

Very Deep Convolutional Networks for Large-Scale Image Recognition

Simonyan, K., & Zisserman, A. (2014) · arXiv · doi:10.48550/arxiv.1409.1556 · Cited by 74,248 · see citing works

Microsoft COCO: Common Objects in Context

Lin, T.-Y., Maire, M., Belongie, S., Hays, J., Perona, P., Ramanan, D., Dollár, P., & Zitnick, C. L. (2014) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-10602-1_48 · Cited by 45,460 · see citing works

Untitled work

(2016) · Cited by 31,590 · see citing works

Human-level control through deep reinforcement learning

Mnih, V., Kavukcuoglu, K., Silver, D., Rusu, A. A., Veness, J., Bellemare, M. G., Graves, A., Riedmiller, M., Fidjeland, A. K., Ostrovski, G., et al. (2015) · Nature · doi:10.1038/nature14236 · Cited by 30,357 · see citing works

Mastering the game of Go with deep neural networks and tree search

Silver, D., Huang, A., Maddison, C. J., Guez, A., Sifre, L., van den Driessche, G., Schrittwieser, J., Antonoglou, I., Panneershelvam, V., Lanctot, M., et al. (2016) · Nature · doi:10.1038/nature16961 · Cited by 15,612 · see citing works

Show and tell: A neural image caption generator

Vinyals, O., Toshev, A., Bengio, S., & Erhan, D. (2015) · 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2015.7298935 · Cited by 6,318 · see citing works

SQuAD: 100,000+ Questions for Machine Comprehension of Text

Rajpurkar, P., Zhang, J., Lopyrev, K., & Liang, P. (2016) · Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing · doi:10.18653/v1/d16-1264 · Cited by 6,208 · see citing works

Long-term recurrent convolutional networks for visual recognition and description

Donahue, J., Hendricks, L. A., Guadarrama, S., Rohrbach, M., Venugopalan, S., Darrell, T., & Saenko, K. (2015) · 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2015.7298878 · Cited by 5,228 · see citing works

Deep visual-semantic alignments for generating image descriptions

Karpathy, A., & Fei-Fei, L. (2015) · 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2015.7298932 · Cited by 4,902 · see citing works

VQA: Visual Question Answering

Antol, S., Agrawal, A., Lu, J., Mitchell, M., Batra, D., Zitnick, C. L., & Parikh, D. (2015) · 2015 IEEE International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2015.279 · Cited by 4,487 · see citing works

Teaching Machines to Read and ComprehendPreprint

Hermann, K. M., Kočiský, T., Grefenstette, E., Espeholt, L., Kay, W., Suleyman, M., & Blunsom, P. (2015) · arXiv (Cornell University) · doi:10.48550/arxiv.1506.03340 · Cited by 2,779 · see citing works

Making the V in VQA Matter: Elevating the Role of Image Understanding in Visual Question Answering

Goyal, Y., Khot, T., Summers-Stay, D., Batra, D., & Parikh, D. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.670 · Cited by 2,287 · see citing works

Stacked Attention Networks for Image Question Answering

Yang, Z., He, X., Gao, J., Deng, L., & Smola, A. J. (2016) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2016.10 · Cited by 2,036 · see citing works

Building End-To-End Dialogue Systems Using Generative Hierarchical Neural Network Models

Serban, I. V., Sordoni, A., Bengio, Y., Courville, A. C., & Pineau, J. (2016) · AAAI Publications (The Association for the Advancement of Artificial Intelligence (AAAI)) · doi:10.1609/aaai.v30i1.9883 · Cited by 1,639 · see citing works

Sequence to Sequence -- Video to Text

Venugopalan, S., Rohrbach, M., Donahue, J., Mooney, R., Darrell, T., & Saenko, K. (2015) · IEEE International Conference on Computer Vision · doi:10.1109/iccv.2015.515 · Cited by 1,507 · see citing works

Flickr30k Entities: Collecting Region-to-Phrase Correspondences for Richer Image-to-Sentence Models

Plummer, B. A., Wang, L., Cervantes, C. M., Caicedo, J. C., Hockenmaier, J., & Lazebnik, S. (2015) · 2015 IEEE International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2015.303 · Cited by 1,444 · see citing works

A Neural Conversational Model

Vinyals, O., & Le, Q. (2015) · arXiv · doi:10.48550/arxiv.1506.05869 · Cited by 1,400 · see citing works

From captions to visual concepts and back

Fang, H., Gupta, S., Iandola, F., Srivastava, R. K., Deng, L., Dollár, P., Gao, J., He, X., Mitchell, M., Platt, J. C., et al. (2015) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2015.7298754 · Cited by 1,305 · see citing works

Hierarchical Question-Image Co-Attention for Visual Question AnsweringPreprint

Lu, J., Yang, J., Batra, D., & Parikh, D. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1606.00061 · Cited by 1,303 · see citing works

How NOT To Evaluate Your Dialogue System: An Empirical Study of Unsupervised Evaluation Metrics for Dialogue Response Generation

Liu, C., Lowe, R., Serban, I. V., Noseworthy, M., Charlin, L., & Pineau, J. (2016) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/d16-1230 · Cited by 1,262 · see citing works

Deep Reinforcement Learning for Dialogue Generation

Li, J., Monroe, W., Ritter, A., Jurafsky, D., Galley, M., & Gao, J. (2016) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/d16-1127 · Cited by 1,221 · see citing works

Translating Videos to Natural Language Using Deep Recurrent Neural Networks

Venugopalan, S., Xu, H., Donahue, J., Rohrbach, M., Mooney, R. J., & Saenko, K. (2015) · Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT) · doi:10.3115/v1/n15-1173 · Cited by 996 · see citing works

A Hierarchical Latent Variable Encoder-Decoder Model for Generating Dialogues

Serban, I. V., Sordoni, A., Lowe, R., Charlin, L., Pineau, J., Courville, A. C., & Bengio, Y. (2017) · AAAI Publications (The Association for the Advancement of Artificial Intelligence (AAAI)) · doi:10.1609/aaai.v31i1.10983 · Cited by 734 · see citing works

Towards AI-Complete Question Answering: A Set of Prerequisite Toy Tasks

Weston, J., Bordes, A., Chopra, S., Rush, A. M., van Merriënboer, B., Joulin, A., & Mikolov, T. (2015) · arXiv · doi:10.48550/arxiv.1502.05698 · Cited by 670 · see citing works

MovieQA: Understanding Stories in Movies through Question-Answering

Tapaswi, M., Zhu, Y., Stiefelhagen, R., Torralba, A. B., Urtasun, R., & Fidler, S. (2016) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2016.501 · Cited by 646 · see citing works

Ask Your Neurons: A Neural-Based Approach to Answering Questions about Images

Malinowski, M., Rohrbach, M., & Fritz, M. (2015) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2015.9 · Cited by 633 · see citing works

Exploring Models and Data for Image Question AnsweringPreprint

Ren, M., Kiros, R., & Zemel, R. S. (2015) · arXiv (Cornell University) · doi:10.48550/arxiv.1505.02074 · Cited by 618 · see citing works

Large-scale Simple Question Answering with Memory Networks

Bordes, A., Usunier, N., Chopra, S., & Weston, J. (2015) · arXiv · doi:10.48550/arxiv.1506.02075 · Cited by 528 · see citing works

Making the V in VQA Matter: Elevating the Role of Image Understanding in Visual Question Answering

Goyal, Y., Khot, T., Agrawal, A., Summers-Stay, D., Batra, D., & Parikh, D. (2019) · International Journal of Computer Vision · doi:10.1007/s11263-018-1116-0 · Cited by 487 · see citing works

Learning End-to-End Goal-Oriented DialogPreprint

Bordes, A., Boureau, Y.-L., & Weston, J. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1605.07683 · Cited by 481 · see citing works

Segmentation from Natural Language Expressions

Hu, R., Rohrbach, M., & Darrell, T. (2016) · Lecture notes in computer science · doi:10.1007/978-3-319-46448-0_7 · Cited by 467 · see citing works

A dataset for Movie Description

Rohrbach, A., Rohrbach, M., Tandon, N., & Schiele, B. (2015) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2015.7298940 · Cited by 450 · see citing works

Are You Talking to a Machine? Dataset and Methods for Multilingual Image Question AnsweringPreprint

Gao, H., Mao, J., Zhou, J., Huang, Z., Wang, L., & Xu, W. (2015) · arXiv (Cornell University) · doi:10.48550/arxiv.1505.05612 · Cited by 437 · see citing works

A Multi-World Approach to Question Answering about Real-World Scenes based on Uncertain InputPreprint

Malinowski, M., & Fritz, M. (2014) · arXiv (Cornell University) · doi:10.48550/arxiv.1410.0210 · Cited by 432 · see citing works

Human Attention in Visual Question Answering: Do Humans and Deep Networks look at the same regions?

Das, A., Agrawal, H., Zitnick, C. L., Parikh, D., & Batra, D. (2016) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/d16-1092 · Cited by 431 · see citing works

Grounding of Textual Phrases in Images by Reconstruction

Rohrbach, A., Rohrbach, M., Hu, R., Darrell, T., & Schiele, B. (2016) · Max Planck Digital Library · Cited by 422 · see citing works

GuessWhat?! Visual Object Discovery through Multi-modal Dialogue

de Vries, H., Strub, F., Chandar, S., Pietquin, O., Larochelle, H., & Courville, A. C. (2017) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2017.475 · Cited by 378 · see citing works

Visual Turing test for computer vision systems

Geman, D., Geman, S., Hallonquist, N., & Laurent Younes, B. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1422953112 · Cited by 323 · see citing works

Yin and Yang: Balancing and Answering Binary Visual Questions

Zhang, P., Goyal, Y., Summers-Stay, D. A., Batra, D., & Parikh, D. (2016) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2016.542 · Cited by 312 · see citing works

The Ubuntu Dialogue Corpus: A Large Dataset for Research in Unstructured Multi-Turn Dialogue Systems

Lowe, R., Pow, N., Serban, I. V., & Pineau, J. (2015) · Annual Meeting of the Special Interest Group on Discourse and Dialogue · doi:10.18653/v1/w15-4640 · Cited by 282 · see citing works

Generating Factoid Questions With Recurrent Neural Networks: The 30M Factoid Question-Answer Corpus

Serban, I. V., García-Durán, A., Gulcehre, C., Ahn, S., Chandar, S., Courville, A., & Bengio, Y. (2016) · Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · doi:10.18653/v1/p16-1056 · Cited by 280 · see citing works

Towards AI-Complete Question Answering: A Set of Prerequisite Toy Tasks

Weston, J., Bordes, A., Chopra, S., Rush, A. M., van Merriënboer, B., Joulin, A., & Mikolov, T. (2016) · International Conference on Learning Representations · Cited by 261 · see citing works

Visual Storytelling

Huang, T.-H., Ferraro, F., Mostafazadeh, N., Misra, I., Agrawal, A., Devlin, J., Girshick, R., He, X., Kohli, P., Batra, D., et al. (2016) · Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT) · doi:10.18653/v1/n16-1147 · Cited by 254 · see citing works

Revisiting Visual Question Answering Baselines

Jabri, A., Joulin, A., & van der Maaten, L. (2016) · Lecture notes in computer science · doi:10.1007/978-3-319-46484-8_44 · Cited by 235 · see citing works

What Are You Talking About? Text-to-Image Coreference

Kong, C., Lin, D., Bansal, M., Urtasun, R., & Fidler, S. (2014) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2014.455 · Cited by 191 · see citing works

Listen, Attend, and Walk: Neural Mapping of Navigational Instructions to Action Sequences

Mei, H., Bansal, M., & Walter, M. R. (2016) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v30i1.10364 · Cited by 184 · see citing works

Smart Reply

Kannan, A., Kurach, K., Ravi, S., Kaufmann, T., Tomkins, A., Miklos, B., Corrado, G. S., Lukacs, L., Ganea, M., Young, P., et al. (2016) · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) · doi:10.1145/2939672.2939801 · Cited by 182 · see citing works

Knowledge Guided Disambiguation for Large-Scale Scene Classification With Multi-Resolution CNNs

Wang, L., Guo, S., Huang, W., Xiong, Y., & Qiao, Y. (2017) · IEEE Transactions on Image Processing · doi:10.1109/tip.2017.2675339 · Cited by 154 · see citing works

Evaluating Prerequisite Qualities for Learning End-to-End Dialog SystemsPreprint

Dodge, J., Gane, A., Zhang, X., Bordes, A., Chopra, S., Miller, A., Szlam, A. D., & Weston, J. (2015) · arXiv (Cornell University) · doi:10.48550/arxiv.1511.06931 · Cited by 150 · see citing works

Image-Grounded Conversations: Multimodal Context for Natural Question and Response GenerationPreprint

Mostafazadeh, N., Brockett, C., Dolan, B., Galley, M., Gao, J., Spithourakis, G., & Vanderwende, L. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1701.08251 · Cited by 125 · see citing works

Joint Video and Text Parsing for Understanding Events and Answering Queries

Tu, K., Meng, M., Lee, M. W., Choe, T. E., & Zhu, S. C. (2014) · IEEE Multimedia · doi:10.1109/mmul.2014.29 · Cited by 113 · see citing works

An ISU dialogue system exhibiting reinforcement learning of dialogue policies

Lemon, O., Georgila, K., Henderson, J., & Stuttle, M. N. (2006) · Conference of the European Chapter of the Association for Computational Linguistics · doi:10.3115/1608974.1608986 · Cited by 95 · see citing works

VizWiz: Nearly Real-time Answers to Visual Questions

Bigham, J. P., Jayant, R., Ji, H., Little, G., Millerγ, A., Miller, R. C., Miller, R., Tatarowicz, A., White, Y., White, S., et al. (2010) · Cited by 80 · see citing works

Sort Story: Sorting Jumbled Images and Captions into Stories

Agrawal, H., Chandrasekaran, A., Batra, D., Parikh, D., & Bansal, M. (2016) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/d16-1091 · Cited by 61 · see citing works

Question Relevance in VQA: Identifying Non-Visual And False-Premise Questions

Ray, A., Christie, G. A., Bansal, M., Batra, D., & Parikh, D. (2016) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/d16-1090 · Cited by 48 · see citing works

Empirical methods for evaluating dialog systems

Paek, T. (2001) · doi:10.3115/1118053.1118054 · Cited by 47 · see citing works

Measuring Machine Intelligence Through Visual Question Answering

Zitnick, C. L., Agrawal, A., Antol, S., Mitchell, M., Batra, D., & Parikh, D. (2016) · AI Magazine · doi:10.1609/aimag.v37i1.2647 · Cited by 29 · see citing works

Resolving Language and Vision Ambiguities Together: Joint Segmentation and Prepositional Attachment Resolution in Captioned Scenes

Christie, G. A., Laddha, A., Agrawal, A., Antol, S., Goyal, Y., Kochersberger, K. B., & Batra, D. (2016) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/d16-1156 · Cited by 17 · see citing works

Grad-CAM: Visual Explanations from Deep Networks via Gradient-Based Localization

Selvaraju, R. R., Cogswell, M., Das, A., Vedantam, R., Parikh, D., & Batra, D. (2020) · International Journal of Computer Vision · doi:10.1007/s11263-019-01228-7 · Cited by 6,909 · see citing works

A Survey on Explainable Artificial Intelligence (XAI): Toward Medical XAI

Tjoa, E., & Guan, C. (2021) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2020.3027314 · Cited by 2,524 · see citing works

Vision-and-Language Navigation: Interpreting Visually-Grounded Navigation Instructions in Real Environments

Anderson, P., Wu, Q., Teney, D., Bruce, J., Johnson, M., Sunderhauf, N., Reid, I., Gould, S., & van den Hengel, A. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2018.00387 · Cited by 1,187 · see citing works

Multimodal learning with transformers: A survey

Xu, P., Zhu, X., & Clifton, D. A. (2023) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2023.3275156 · Cited by 1,072 · see citing works

Graph R-CNN for Scene Graph Generation

Yang, J., Lu, J., Lee, S., Batra, D., & Parikh, D. (2018) · Lecture notes in computer science · doi:10.1007/978-3-030-01246-5_41 · Cited by 889 · see citing works

Scaling Egocentric Vision: The "Equation missing" Dataset

Damen, D., Doughty, H., Farinella, G. M., Fidler, S., Furnari, A., Kazakos, E., Moltisanti, D., Munro, J., Perrett, T., Price, W., et al. (2018) · Lecture notes in computer science · doi:10.1007/978-3-030-01225-0_44 · Cited by 875 · see citing works

Flamingo: a visual language model for few-shot learning

Alayrac, J.-B., Donahue, J., Luc, P., Miech, A., Barr, I., Hasson, Y., Lenc, K., Mensch, A., Millican, K., Reynolds, M., et al. (2022) · Advances in Neural Information Processing Systems 35 · doi:10.52202/068431-1723 · Cited by 966 · see citing works

Intern VL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic Tasks

Chen, Z., Wu, J., Wang, W., Su, W., Chen, G., Xing, S., Zhong, M., Zhang, Q., Zhu, X., Lu, L., et al. (2024) · 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr52733.2024.02283 · Cited by 734 · see citing works

VizWiz Grand Challenge: Answering Visual Questions from Blind People

Gurari, D., Li, Q., Stangl, A. J., Guo, A., Lin, C., Grauman, K., Luo, J., & Bigham, J. P. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2018.00380 · Cited by 621 · see citing works

Reinforced Cross-Modal Matching and Self-Supervised Imitation Learning for Vision-Language Navigation

Wang, X., Huang, Q., Celikyilmaz, A., Gao, J., Shen, D., Wang, Y.-F., Wang, W. Y., & Zhang, L. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2019.00679 · Cited by 522 · see citing works

TGIF-QA: Toward Spatio-Temporal Reasoning in Visual Question Answering

Jang, Y., Song, Y., Yu, Y., Kim, Y., & Kim, G. (2017) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2017.149 · Cited by 496 · see citing works

Inferring and Executing Programs for Visual Reasoning

Johnson, J., Hariharan, B., van der Maaten, L., Hoffman, J., Fei-Fei, L., Zitnick, C. L., & Girshick, R. (2017) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2017.325 · Cited by 487 · see citing works

Counterfactual VQA: A Cause-Effect Look at Language Bias

Niu, Y., Tang, K., Zhang, H., Lu, Z., Hua, X., & Wen, J.-R. (2021) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr46437.2021.01251 · Cited by 445 · see citing works

Convolutional Image Captioning

Aneja, J., Deshpande, A., & Schwing, A. G. (2018) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2018.00583 · Cited by 426 · see citing works

Neural Baby Talk

Lu, J., Yang, J., Batra, D., & Parikh, D. (2018) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2018.00754 · Cited by 412 · see citing works

Cross-Modal Causal Relational Reasoning for Event-Level Visual Question Answering

Liu, Y., Li, G., & Lin, L. (2023) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2023.3284038 · Cited by 354 · see citing works

MUREL: Multimodal Relational Reasoning for Visual Question Answering

Cadene, R., Ben-younes, H., Cord, M., & Thome, N. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2019.00209 · Cited by 330 · see citing works

VLP: A Survey on Vision-language Pre-training

Chen, F., Zhang, D., Han, M., Chen, X.-Y., Shi, J. C., Xu, S., & Xu, B. (2023) · Machine Intelligence Research · doi:10.1007/s11633-022-1369-5 · Cited by 295 · see citing works

Fashion IQ: A New Dataset Towards Retrieving Images by Natural Language Feedback

Wu, H., Gao, Y., Guo, X., Al-Halah, Z., Rennie, S. J., Grauman, K. L., & Feris, R. (2021) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr46437.2021.01115 · Cited by 297 · see citing works

VLN↻BERT: A Recurrent Vision-and-Language BERT for Navigation

Hong, Y., Wu, Q., Qi, Y., Rodriguez-Opazo, C., & Gould, S. (2021) · 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr46437.2021.00169 · Cited by 264 · see citing works

Large-scale Multi-modal Pre-trained Models: A Comprehensive Survey

Wang, X., Chen, G., Qian, G., Gao, P., Wei, X.-Y., Wang, Y., Tian, Y., & Gao, W. (2023) · Machine Intelligence Research · doi:10.1007/s11633-022-1410-8 · Cited by 245 · see citing works

Explainable AI in medical imaging: An overview for clinical practitioners – Beyond saliency-based XAI approaches

Borys, K., Schmitt, Y. A., Nauta, M., Seifert, C., Krämer, N., Friedrich, C. M., & Nensa, F. (2023) · European Journal of Radiology · doi:10.1016/j.ejrad.2023.110786 · Cited by 233 · see citing works

Neural Approaches to Conversational AI: Question Answering, Task-oriented Dialogues and Social Chatbots

Gao, J., Galley, M., & Li, L. C. (2019) · Foundations and Trends® in Information Retrieval · doi:10.1561/1500000074 · Cited by 44 · see citing works

CPT: Colorful Prompt Tuning for pre-trained vision-language models

Yao, Y., Zhang, A., Zhang, Z., Liu, Z., Chua, T., & Sun, M. (2024) · AI Open · doi:10.1016/j.aiopen.2024.01.004 · Cited by 206 · see citing works

Audio Visual Scene-Aware Dialog

Alamri, H., Cartillier, V., Das, A., Wang, J., Cherian, A., Essa, I. A., Batra, D., Marks, T. K., Hori, C., Anderson, P., et al. (2019) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2019.00774 · Cited by 172 · see citing works

Engaging Image Captioning via Personality

Shuster, K., Humeau, S., Hu, H., Bordes, A., & Weston, J. (2019) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2019.01280 · Cited by 160 · see citing works

Visual Coreference Resolution in Visual Dialog Using Neural Module Networks

Kottur, S., Moura, J. M. F., Parikh, D., Batra, D., & Rohrbach, M. (2018) · Lecture notes in computer science · doi:10.1007/978-3-030-01267-0_10 · Cited by 161 · see citing works

Vision-Language Pre-Training: Basics, Recent Advances, and Future Trends

Gan, Z., Li, L., Li, C., Wang, L., Liu, Z., & Gao, J. (2022) · Foundations and Trends® in Computer Graphics and Vision · doi:10.1561/0600000105 · Cited by 155 · see citing works

Two Causal Principles for Improving Visual Dialog

Qi, J., Niu, Y., Huang, J., & Zhang, H. (2020) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr42600.2020.01087 · Cited by 150 · see citing works

Parallel Attention: A Unified Framework for Visual Object Discovery Through Dialogs and Queries

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Reasoning Visual Dialogs With Structural and Partial Observations

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